Machine learning is a subset of Artificial Intelligence (AI) that focuses on building systems that learn or improve performance based on the data they consume.

Machine learning is a technique that discovers previously unknown relationships in data. Some relationships may be known, but the algorithm learns those patterns, example, for inferencing. Machine learning and AI are often discussed together. An important distinction is that although all machine learning is AI, not all AI is machine learning. Artificial intelligence refers to the implementation and study of systems that exhibit autonomous intelligence or behavior of their own. Machine learning deals with techniques that enable devices to learn from their own performance and modify their own functioning. Machine learning automatically searches potentially large stores of data to discover patterns and trends that go beyond simple statistical analysis. Machine learning uses sophisticated algorithms that identify patterns in data creating models. Those models can be used to make predictions and forecasts, and categorize data.

To compare machine learning with Generative AI (GenAI), GenAI is specifically designed for producing new content like text, code, or images by generative AI models, which are trained on vast data sets to create original outputs based on patterns they learn; essentially, one is about making predictions based on data, while the other is about creating new data based on learned patterns. Oracle Machine Learning concentrates on traditional machine learning tasks like prediction and classification using established algorithms.

The key features of machine learning are:

• Automatic discovery of patterns

• Prediction of likely outcomes

• Creation of actionable information

• Ability to analyze potentially large volumes of data

Machine learning can answer questions that cannot be addressed through traditional deductive query and reporting techniques.